Brain-computer interfaces (BCIs) are like translators between our brains and machines. They need to be super accurate to be useful. But, using just one type of model to read brain signals isn't always the best. That's where hybrid models come in. They combine different types of models to get better results. One exciting area is mixing convolutional neural networks (...
Skin cancer is a widespread and potentially deadly condition. It is crucial to catch it early for successful treatment. Skin cancer makes up 1 in 5 of all cancer cases worldwide. Melanoma alone causes over 60, 000 deaths each year. This highlights the need for effective early detection methods. Traditional skin cancer screening by doctors is time-consuming and cos...
Brain tumors are sneaky. They can hide in MRI scans, making it tough for doctors to spot them early. This is a big deal because catching them early can make a huge difference in treatment success. Deep learning models have been trying to help, but they face some serious hurdles. These include not having enough varied data, having more of one type of tumor than anothe...
Medical image classification has seen a huge boost from deep convolutional neural networks (CNNs). These networks are like super-smart detectors that can spot patterns in medical images. However, there are two big hurdles to overcome. First, medical data from different places isn't always the same. This is because each hospital or clinic might have different types of...
Skin is our body's biggest shield against the outside world. It guards us from harm, but what happens when it's under attack? Skin diseases can be a real pain, both physically and mentally. The problem is, diagnosing these conditions can be a puzzle. Why? Because skin lesions can look different on everyone, and symptoms often mix and match. Plus, teaching computers t...
Measuring temperature in large spaces like a room can be tricky. Traditional methods using emission spectroscopy can't give a full view. Scientists found a smarter way using data from spectroscopy. They tried two approaches. First, they used something called feature engineering, which is like finding the best bits of data, with classic machine learning models. Second...
Imagine if detecting skin cancer could be as simple as snapping a picture. Scientists are working on just that! They're using a special kind of computer program called convolutional neural networks (CNNs), and these aren't your average programs. They're like super-smart detectives that can spot patterns in images, like skin lesions. But how do they make these progra...
Breast cancer is a major health concern for women worldwide, including those in Taiwan. Early detection is key, and imaging techniques like mammograms and ultrasounds play a big role. But, these methods alone aren't perfect. To make diagnosis better, scientists are combining these two methods. This is called cross-modality fusion. Researchers used pictures from publ...
You know how when it's raining or snowing, it's hard to see clearly in videos? Well, scientists have been trying to fix this using something called convolutional neural networks (CNNs). The problem is, these networks can only handle single images and don't really understand the difference between one video frame and the next. Plus, they can only deal with one type of...
Have you ever thought about how you read and understand documents? Humans can easily connect ideas across paragraphs, tables, and even figures. But getting machines to do the same thing isn't so simple. Traditionally, different machine learning techniques were used for different parts of a document—like language models for paragraphs and convolutional neural networks...