AZoOptics

Open Mouse Brain Dataset Advances AI-Based Neuron Reconstruction

A difficulty-graded mouse brain dataset pairs 3D microscopy images with verified neuron reconstructions to support AI-driven ...

AI deciphers long-range DNA signals behind RNA splicing

Accurate RNA splicing is essential for gene expression and human health, yet predicting how DNA sequence variations affect ...
Tech Times

Qualcomm Closes $3.9 Billion Modular Deal: Meta Validates Full-Stack CUDA Challenge

Qualcomm confirmed a $3.92 billion all-stock deal to buy AI software startup Modular, paired with a Meta Platforms CPU ...
GitHub

PhaseNet: A Deep-Neural-Network-Based Seismic Arrival Time Picking Method

Zhu, Weiqiang, and Gregory C. Beroza. "PhaseNet: A Deep-Neural-Network-Based Seismic Arrival Time Picking Method." arXiv preprint arXiv:1803.03211 (2018). Liu, Min, et al. "Rapid characterization of ...

OpenCV 5.0 brings LLMs to the Computer Vision Library

Version 5.0 Modernizes DNN Engine, Adds LLM/VLM Support, and Enhances Core, Hardware Acceleration, and 3D Stack.
IEEE

Enhancing Fraud Detection in Banking With Deep Learning: Graph Neural Networks and Autoencoders for Real-Time Credit Card Fraud Prevention

Abstract: Under the umbrella of artificial intelligence (AI), deep learning enables systems to cluster data and provide incredibly accurate results. This study explores deep learning for fraud ...
VentureBeat

DeepSeek-V4 arrives with near state-of-the-art intelligence at 1/6th the cost of Opus 4.7, GPT-5.5

On standard, cache-miss pricing, DeepSeek-V4-Pro comes in at roughly one-seventh the cost of GPT-5.5 and about one-sixth (1/6th) the cost of Claude Opus 4.7. With cached input, the gap widens: ...
GitHub

NNGP: Deep Neural Network Kernel for Gaussian Process

See also Neural Tangents: Fast and Easy Infinite Neural Networks in Python (ICLR 2020) available at github.com/google/neural-tangents for more up-to-date progress on ...
Electronic Design

A Neural-Network-Based Approach to Smarter DPD Engines

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.
Hosted on MSN

Dropout In Neural Networks — Prevent Overfitting Like A Pro (With Python)

This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch. Dropout in Neural Network is a regularization technique in Deep Learning to ...
Searchenginejournal.com

How To Automate SEO Keyword Clustering By Search Intent With Python

There’s a lot to know about search intent, from using deep learning to infer search intent by classifying text and breaking down SERP titles using Natural Language Processing (NLP) techniques, to ...
Hosted on MSN

Build A Deep Neural Network From Scratch In Python — No Tensorflow!

Step-by-step coding a full deep neural network with zero libraries — just logic and Python. #NeuralNetwork #PythonCode #DeepLearning Trump announces two new national holidays, including one on ...