The performance of these cameras is also quite average. Video recording is limited to p 30fps, which is a bit disappointing, given that the more affordable Narzo 30 offers better options. Battery life is quite good, but charging this phone using the bundled 18W charger takes over two hours. The Oppo Reno 6 Pro is one of the slimmest and lightest phones in its class, and has the looks to go with that. Games ran very well too. Despite the slim body, the back of the phone never got overly hot even after extended gaming sessions.
I found the battery life of the Reno 6 Pro to be pretty solid too. I was easily able to get about a day and half of use, which involved lots of video watching and checking social apps. The camera setup on the Oppo Reno 6 Pro is pretty much identical to that of the Reno 5 Pro, except for the new Bokeh Flare Portrait filter which is fun and works well. The Dimensity SoC is great for gaming and general productivity. You get a mAh battery and 50W fast charging, with a 65W charger unit supplied in the retail box.
Battery life is excellent and you should be able to last well over a single day on each charge. Stereo speakers make games and movies more engaging.
Realme UI's default apps do throw up some spammy notifications but there are lots of features too. The cameras are disappointing overall, especially in low light. You also might not like the plastic rear panel which doesn't feel too premium. The design gives off strong iPhone 12 vibes, but it really seems to work in its favour. The 4,mAh battery capacity might not sound too impressive, but with day-to-day usage, I was easily averaging more than a full day on single charge.
The Oppo Reno 6 misses out on the rear depth camera that the Reno 6 Pro has, but apart from this, it has the same set of sensors on the front and back. The Realme Narzo 30 is a good budget smartphone keeping in mind the hardware that it offers and its competitive price. The design and finish are a big leap from its predecessor, the Narzo 20, and this phone looks attractive despite being made from plastic.
The 90Hz display is a nice addition and makes the software experience fluid. The Narzo 30 is good enough for mid-level gaming, handling most graphics-intensive mobile titles well. However, the phone does get quite hot when stressed. Camera performance is quite average for its segment. The Narzo 30 can take good photos in daylight, but only manages noisy and murky shots in low light.
Video performance is decent at best when shooting in 4K. The Narzo 30 with its 5,mAh battery offers good battery life, managing 1. Charging is relatively quick, going from a dead battery to a full charge in 1 hour and 10 minutes using the bundled 30W charger. The Moto G60 s the first Motorola smartphone with a megapixel camera and is priced quite aggressively. The Moto G60 is a big and bulky phone measuring 9. This makes single-handed use a little tough.
It has a big 6. It has a hole punch at the top that houses the megapixel selfie camera. Moto G60 is powered by the tried and tested Qualcomm Snapdragon G processor and delivers good performance.
Storage is further expandable using the hybrid SIM slot. The Moto G60 houses a 6,mAh battery which makes it bulky. The battery offers a day and a half worth of battery life but charging time is long as the phone only gets a 20W charger in the box. The Moto G60 has a triple camera setup at the back but does the job of four cameras.
It has a megapixel primary camera, an 8-megapixel ultra-wide angle camera that also clicks macros, and a depth sensor. Photos clicked from the Moto G60 were average and not as sharp as some of the other competition in daylight. The ultra-wide angle photos are upscaled to megapixels and had some distortion. Lowlight photos were also average as the phone failed to get the colour tone right. Night mode does not return a brighter image but fixes the colour tone issue.
Motorola ships the Moto G60 with Android 11 with only the Facebook app pre-installed. This is a big plus considering most of the completion has spammy bloatware preinstalled. The Xiaomi Mi 11X offers the very powerful Qualcomm Snapdragon SoC at a surprisingly low price, and the tradeoff is camera quality.
While this phone is great for gaming and entertainment, it takes just about average photos and videos in the daytime, while low-light performance is quite below par.
You get a big, bright vibrant 6. There are also some premium touches such as Gorilla Glass 5 on the front and back, an IP53 rating, and stereo speakers. Games run very well, and videos look great on the screen. The megapixel main rear camera is serviceable and the 8-megapixel ultra-wide camera is much weaker, but the surprise standout is the 5-megapixel "telemacro" camera which allows for some very creative shots. The Redmi Note 10S is a slightly more powerful version of the Redmi Note 10 and both these devices are identical to look at.
It does have a fair amount of preinstalled apps that occasionally push spammy notifications. The Note 10S has a 5,mAh battery and comes with a 33W charger in the box. Xiaomi offers a quad-camera setup on the Redmi Note 10S with a megapixel primary sensor. Daylight shots were average but oversharpened and distant objects appeared blotchy. Close-up and macro shots fared better. Low light shots appeared flat and grainy but had some improvements with Night mode.
Overall, the Redmi Note 10S is worth buying over the Redmi Note 10 only for its improved performance. While the iQoo Z3 does not follow in the footsteps of the gamer-centric iQoo 3, it succeeds as an affordable smartphone that not only looks good, but also offers a good processor considering its price. This is where the other interesting hardware bits of the iQoo Z3 come in. The 4,mAh battery charges to percent in just 60 minutes using the included 55W charging adapter.
Factor in that attractive price tag, and iQoo seems to have a solid contender. Vivo's gimbal camera system was a big hit in the company's X50 series, and it has gotten even better in the latest X60 series. It also has Corning Gorilla Glass 6 at the back which gives the smartphone superior drop protection. The gimbal camera system on the Vivo X60 Pro comprises a megapixel Sony IMX sensor that physically moves to compensate for minor shakes. It also has a megapixel ultra-wide angle camera and a megapixel portrait camera.
The Vivo X60 Pro clicks very good photos and should be your first pick if you intend to shoot a lot of videos. Realme 8 Pro is the successor to the Realme 7 Pro and gets a bold design. It is slimmer than its predecessor and comes in flashy colours. The main change on the Realme 8 Pro is the quad-camera setup at the back which houses a megapixel primary camera. The phone is light and easy to hold.
It sports a 6. You get a 4,mAh battery that is capable of fast charging at 50W. The camera performance is a hit or miss with the Realme 8 Pro. Daylight photos were average and did not have as much detail. The phone does a good job with portrait shots and the macros too were sharp but limited to 2-megapixels in resolution. Camera performance in low light was decent with better details in nighmode.
Realme 8 Pro managed to deliver good battery life and lasted for 26 hours and 14 minutes in our HD video loop test. The 50W bundled charger is quick to charge the phone up getting it to 75 percent in 30 minutes. The main selling point of the Poco X3 Pro is its Qualcomm Snapdragon SoC, which is a slightly faster version of the erstwhile flagship Snapdragon This makes the X3 Pro perform very well in benchmarks and even in real-world tasks, including high-end games.
You should have more than enough power to get through all your day-to-day activities. Battery life is also quite good, but the large battery makes this phone heavy and bulky.
You don't get 5G which might make this phone seem to lag behind some of its competitors. Its quality is serviceable but not as good as some others at this price level. Similarly, the cameras deliver acceptable performance but photo and video quality aren't strong points of the Poco X3 Pro.
With its eye-catching design and prominent camera bump, the Poco X3 Pro will appeal to young buyers who want performance above all else. Xiaomi is raising the profile of its mainstream Redmi Note series with specifications that are sure to grab attention. The Redmi Note 10 Pro Max has a megapixel camera but is otherwise identical to the Redmi Note 10 Pro, and the price difference between the two might not be worth it.
This phone has a fantastic 6. It's bright, crisp, and vibrant. There's a mAh battery and you get a 33W charger in the box. The rear megapixel camera takes good shots in the daytime but don't expect incredible detail in distant objects. The 5-megapixel telemacro camera is even more interesting and really does allow for some creative framing.
Performance overall in everyday use is pretty good, and so is battery life. The phone heats up a bit when gaming. The body is slim and light, and this makes the Redmi Note 10 Pro Max easy to use and carry around. With only cosmetic changes and a slightly upgraded processor compared to the OnePlus 8T, the new OnePlus 9R is not very exciting at first. It has been launched exclusively in India because the OnePlus 9 and 9 Pro have come in at higher prices.
The company could have done more to keep things fresh in the premium segment, but even so, the 9R is a good overall package. Performance is good in everyday tasks and games run well too. The battery will last you all day, and you get a 65W fast charger in the box. The megapixel main camera takes good shots and Nightscape mode can work very well depending on ambient light conditions. OxygenOS continues to be slick and feature-rich without getting overbearing.
The 9R could be a good choice if you're a OnePlus fan, but do keep in mind that there's a lot of competition and you have many other choices. The Redmi Note 10 isn't pathbreaking in terms of features and specifications for the sub-Rs. It's slimmer and lighter than the Redmi Note 9, and debuts a new 'Evol' design language which makes it look quite smart.
You get a Qualcomm Snapdragon SoC which is powerful enough for casual gaming as well as everyday tasks. Battery life is good enough to get you through at least a full day, and charging is quick. The cameras are quite ordinary, with the megapixel primary one taking good shots in the daytime ad acceptable ones at night. The ultra-wide and selfie cameras are also serviceable, but the macro one is just for amusement.
MIUI is still full of promotional content and ads, but the company promises to remove these with a future update. The new Galaxy A52 has a big 6.
It also has a fast 90Hz refresh rate. The build is mainly plastic which isn't the case with its competition. The smartphone has a 4,mAh battery and is manageable for single-handed use.
The battery is capable of fast charging at 25W but you only get a 15W charger in the box. The Galaxy A52 has a quad-camera setup at the back consisting of a megapixel primary camera, a megapixel ultra-wide angle camera, a 5-megapixel macro camera and a 5-megapixel depth sensor. The camera performance is acceptable in daylight but the wide-angle camera does not capture as much detail as the primary camera. Close-up were good and the Galaxy A52 clicks some good portraits.
The macro camera too was good in delivering a crisp output. Selfies taken from the selfie camera were good and the camera did a good job in most lighting conditions.
The Galaxy A52 is powered by a Qualcomm Snapdragon processor which is a decent processor. Compared to some of the direct competitors of the Galaxy A52, the chipset feels underpowered. The 4,mAh battery delivers good battery life and the phone went for about a day and a half with our usage. Charging times weren't too long either with the charger topping the phone up in about an hour and a half. The Samsung Galaxy A72 has an in-display fingerprint sensor, but I found it to be very inconsistent with authentication and a bit sluggish too.
Age rating For all ages. Installation Get this app while signed in to your Microsoft account and install on up to ten Windows 10 devices. Language supported English United States.
Additional terms Terms of transaction Mole Hit license terms. Seizure warnings Photosensitive seizure warning. Report this product Report this game to Microsoft Thanks for reporting your concern. Our team will review it and, if necessary, take action. Sign in to report this game to Microsoft. This may cause the model overfitting problem. This study developed the mole detection and segmentation software DiaMole using the Python programming language version 3.
Two major Python packages TensorFlow version 1. DiaMole was developed and tested on the two mainstream operating systems Windows 7 and Windows DiaMole has a few prerequisite Python packages, including Numpy and Pillow.
To provide an easy installation procedure, we used the software Anaconda Distribution version 4. The first main task of DiaMole was object detection, and three popular object detection algorithms were integrated. The popular object detection algorithm YOLOv3 You Only Look Once [ 13 ] calculated the bounding box of an object at three scales, as similar to the feature pyramid networks [ 14 ]. YOLOv3 ran very fast to accurately predict the objects and their class labels in the given image. Its object detection performance was better than the previous version, the fast region convolutional neural network [ 15 ].
Lin et al. RetinaNet matched the running speed of the previous one-stage object detection networks but achieved a better object detection accuracy [ 16 ]. The main contribution of RetinaNet was a new focal loss function that reduced the training bias caused by the dataset imbalance and rapidly focused the model training process on the difficult samples. The detection results of all the above three object detection algorithms might be integrated using the Non-Maximum Suppression NMS strategy to generate the consensus object bounding boxes [ 17 ].
The integration procedure was denoted as the algorithm ALL. The dataset MoleMapper did not provide the mole masks and labels, and this study transferred a publicly available segmentation model from the ISIC challenge [ 18 ]. The pretrained VGG model was chosen as the base model in this study [ 19 ]. A mole usually occupied the major part of a dermoscopic image, but a mobile phone skin image may cover the large neighboring regions of a few moles.
So this study firstly got the bounding boxes of the moles using the above object detection algorithms. Then each bounding box was regarded as a dermoscopy-like image and fed to the segmentation model. This model was implemented using the Python programming language version 3.
The following Python packages were used in the above-mentioned UNet model: Tensorflow version 1. The default workflow is to detect the moles in a given human skin image.
This image may be captured by a mobile phone. In the second step, the UNet model will get the precise boundary of each mole, whose bounding box is cropped by the detection algorithms. Besides, the user can draw the bounding boxes based on their own experiences for the moles which are not detected by the algorithms. All the annotations could be saved to local database. All the intermediate data are stored in the local database. The user may export the masks and annotations of the detected moles for further analysis.
The user can export the masks, bounding boxes, and annotations of the detected moles to a word file. This section described the data analysis and annotation protocol using the proposed software DiaMole. The experimental data of DiaMole on multiple datasets were described and discussed in the following sections. Step 1. The left region consists of two buttons and one text box.
The below part is the visualization region, and there are three pages for the raw image raw , images with bounding boxes detect , and images for manual curation draw. The detected moles are enumerated in the text box in the below part so that the user may click to choose each detected mole.
Step 2. Choose an image to analyze, as shown in Figure 2 b. Step 3. Detect and segment the moles in the given image, as shown in Figure 3. Click the button to choose the object detection algorithm. There is only one mole segmentation algorithm UNet, and the mole in each bounding box is automatically segmented.
Step 4. Define a bounding box for a candidate mole missed by DiaMole, as shown in Figure 4. The user may then use the mouse to draw a rectangle to cover a candidate mole in the image, as shown in Figure 4 b. DiaMole asks whether the user wants to save this rectangle as a candidate mole. Step 5. The masks and annotations of all the candidate moles will be saved into the local database. Step 6. The masks and annotations of all the candidate moles will be exported as an annotation report, and the data may be analyzed by other tools.
Step 7. DiaMole used three popular object detection algorithms to detect the two types of objects in the MoleMapper dataset. The mAP is widely used in measuring the object detection algorithms [ 13 , 15 , 16 ].
In the detection of moles and coins, curves can be drawn for every class according to recall and precision. We can get the positions of the coins and moles in the images by these algorithms.
During the training phase of YOLOv3, we used the momentum to optimize the weights. The learning rate was 0. When training the Faster R-CNN, we used the momentum to optimize the weights, set the learning rate to 0.
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