Whenever I pack my camera bag at the last minute for a shoot, I inevitably forget something. Whether that's a specific lens or sometimes even batteries or a memory card, it's always best to prepare. This video from Canadian photographer Justin Laurens shows you how to do just that.
In my quest for a pocketable camera that doesn't also take phone calls, I've arrived at Camp Sony. While I wanted the camera that every tech writer calls one of the best point and shoots ever made, the RX100 VII, between stock and price, I actually arrived at its video focused cousin, the ZV-1. And it makes me wonder: Why don't we have more of these kinds of cameras?
I go through many a season with my gear. Sometimes it's Nikon season; other times, it's Panasonic or Fuji season. But no matter how many times I try to downsize, I always end up back where I started: with too many cameras.
There's always been a gaping hole in Canon's APS-C strategy. While there are plenty of competent APS-C cameras from the company, it hasn't always produced the professional lenses to match the bodies.
By: Khan, Muhammad Adnan, Wasim Ahmad, Taher M., Nankana Sahib
Skin diseases impact millions of people around the world and pose a severe risk to public health. These diseases have a wide range of effects on the skin’s structure, functionality, and appearance. Identifying and predicting skin diseases are laborious processes that require a complete physical examination, a review of the patient’s medical history, and proper laboratory diagnostic testing. Additionally, it necessitates a significant number of histological and clinical characteristics for examination and subsequent treatment. As a disease’s complexity and quantity of features grow, identifying and predicting it becomes more challenging. This research proposes a deep learning (DL) model utilizing transfer learning (TL) to quickly identify skin diseases like chickenpox, measles, and monkeypox. A pre-trained VGG16 is used for transfer learning. The VGG16 can identify and predict diseases more quickly by learning symptom patterns. Images of the skin from the four classes of chickenpox, measles, monkeypox, and normal are included in the dataset. The dataset is separated into training and testing. The experimental results performed on the dataset demonstrate that the VGG16 model can identify and predict skin diseases with 93.29% testing accuracy. However, the VGG16 model does not explain why and how the system operates because deep learning models are black boxes. Deep learning models’ opacity stands in the way of their widespread application in the healthcare sector. In order to make this a valuable system for the health sector, this article employs layer-wise relevance propagation (LRP) to determine the relevance scores of each input. The identified symptoms provide valuable insights that could support timely diagnosis and treatment decisions for skin diseases.
There are so many times I've asked myself: If I were starting fresh, would I end up within the same system of gear that I'm using now? When I started photography, Sony wasn't even a player in the DSLR game, and so inertia has invariably led me to (mostly) Canon and Nikon over the years. But today's new photographers are spoiled for choice. Which way to go? One take on that question comes from landscape and street photographer Arnulfur Hakonarson, aka THAT ICELANDIC GUY on YouTube. As a Sony shooter, he recommends starting out with one of their budget APS-C models, such as the a6400 or a6300.
About four months ago, I downgraded my phone. I went from what would be considered a more photography-oriented phone, the iPhone 14 Pro, to the less photo-feature-rich iPhone 13 Mini. I don’t miss the photography pieces of the phone at all, and I’ll bet you won’t either. I’m aware that this is a hot take. My primary reason for downgrading is that the larger iPhone never quite felt right in my hand. The Goldilocks “just right” size of the iPhone 12 Mini was always perfect in my hands, so when I saw a good-condition iPhone 13 Mini for sale, I jumped on it.