Researchers develop new 'emotionally aware' model for classifying mental health conditions

Researchers have developed a new "emotionally aware" AI-based model for classifying mental health conditions, which could ...
Tech Times

DeepSeek V4 Architecture: How Sparse Attention Cuts Inference Costs, What NIST Found

DeepSeek V4 architecture uses sparse attention to cut inference costs 73% at one-million-token contexts, but a NIST ...
Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
Morning Overview on MSN

A research ship off Brazil pulled 31 new deep-sea species from the ocean’s least-explored layer

Scientists aboard a research vessel off the coast of Brazil identified 31 previously unknown species during just two weeks of ...
The New York Times

‘Deep Water’ Review: Prepare for an Emergency Landing, With Fins

The action director Renny Harlin combines two different kinds of disaster movies, with lots of gory shark scenes. By Glenn Kenny When you purchase a ticket for an independently reviewed film through ...
Frontiers

Chlamy_ChloroPred: a deep learning-based, highly accurate binary classifier for chloroplast protein prediction in the model microalga, Chlamydomonas reinhardtii, with potential ...

The chloroplast, a living relic of an ancient endosymbiotic interaction between a microalga and a microbe and the principal subcellular organelle responsible for biological CO 2 assimilation, is ...
LinkedIn

DeepDigitsNet – A Deep Learning Classifier for Handwritten Digits

The goal of this project was to build a deep learning model that can classify handwritten digits (0–9) using the MNIST dataset. This project helped me understand how different activation functions and ...
LinkedIn

Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions

Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is nowadays considered as a core technology of today’s Fourth Industrial Revolution (4IR or Industry 4.0). Due to ...
Nature

Predicting critical transitions with machine learning trained on surrogates of historical data

Critical transitions can occur in many natural and man-made systems. Generic early warning signals motivated by dynamical systems theory have had mixed success on real noisy data. More recent studies ...
IEEE

Shortcut Learning in Binary Classifier Black Boxes: Applications to Voice Anti-Spoofing and Biometrics

Abstract: The widespread adoption of deep-learning models in data-driven applications has drawn attention to the potential risks associated with biased datasets and models. Neglected or hidden biases ...
IEEE

A Novel and Efficient Multi-Target Backdoor Attack for Deep Learning-Based Wireless Signal Classifiers

Abstract: Deep learning (DL)-based wireless signal classification is increasingly becoming important and deployed on edge devices (e.g., IoT, smartphones, etc.) to enhance communication reliability ...
Scientific Research Publishing

Fanai, H. and Abbasimehr, H. (2023) A Novel Combined Approach Based on Deep Autoencoder and Deep Classifiers for Credit Card Fraud Detection. Expert Systems with Applications ...

ABSTRACT: The rapid growth of technology impacts all aspects of modern life, including banking and financial transactions. While these industries benefit significantly from technological advancements, ...