Remote Sensing Image Retrieval remains a challenging topic due to the special nature of Remote Sensing Imagery. Such images contain various different semantic objects, which clearly complicates the retrieval task. In this paper, we present an image r...
Dec 20, 2008 · The tranny is freshly rebuilt, and has only been driven about 500 feet. The pan is a brand new deep GM unit. Common problem? The builder used a cork gasket, is there anything better out …
Whether you’re looking for a spark of inspiration with reels or want to dive deeper into something you already love with Marketplace or in groups, you can discover ideas, experiences and people...
The ability to predict the future trajectory of a patient is a key step toward the development of therapeutics for complex diseases such as Alzheimer's disease (AD). However, most machine learning approaches developed for prediction of disease progre...
Up to now, modern Machine Learning is mainly based on fitting high dimensional functions to enormous data sets, taking advantage of huge hardware resources. We show that biologically inspired neuron models such as the Leaky-Integrate-and-Fire (LIF) n...
Python/Keras implementation of integrated gradients presented in "Axiomatic Attribution for Deep Networks" for explaining any model defined in Keras framework. (⭐ 217)
In this paper a comparative study of the performance of three Convolutional Neural Network models, ResNet50, Inception v3 and VGG19 for classification of skin images with lesions affected by psoriasis is presented. The images used for training and va...
The physics chapter of the NUSEL-Homestake Reference Design Science Book describes the physics motivation for building a deep underground science and engineering laboratory. It includes discussions of outstanding problems in neutrino physics and as...
Deep Learning 101 with PaddlePaddle （『飞桨』深度学习框架入门教程） (⭐ 2753)
Rapid Single Flux Quantum (RSFQ) circuits are the most evolved superconductor logic family. However, the need to clock each cell and the deep pipeline causes a complex clock network with a large skew. This results in lower throughput and high latency...
The recent renaissance in generative models, driven primarily by the advent of diffusion models and iterative improvement in GAN methods, has enabled many creative applications. However, each advancement is also accompanied by a rise in the potential...
gloom•y (glo̅o̅′ mē), adj., gloom•i•er, gloom•i•est. dark or dim; deeply shaded: gloomy skies. causing gloom; dismal or depressing: a gloomy prospect. filled with or showing gloom; sad, dejected, or …
GLOOMY definition: dark or dim; deeply shaded. See examples of gloomy used in a sentence.
This report introduces VitalLens 2.0, a new deep learning model for estimating physiological signals from face video. This new model demonstrates a significant leap in accuracy for remote photoplethysmography (rPPG), enabling the robust estimation of...
An educational resource to help anyone learn deep reinforcement learning. (⭐ 11628)
Many deep learning models have achieved dominant performance on the offline beat tracking task. However, online beat tracking, in which only the past and present input features are available, still remains challenging. In this paper, we propose BEAt...
Feb 18, 2026 · The former Ukrainian army general widely seen as the top political rival to President Volodymyr Zelenskyy has spoken publicly for the first time about a deep rift between the two men.
Deep Learning models to detect hate speech in tweets (⭐ 219)
The classification of streets on road networks has been focused on the vehicular transportational features of streets such as arterials, major roads, minor roads and so forth based on their transportational use. City authorities on the other hand hav...
Conferences are deeply connected to research fields, in this case bibliometrics. As such, they are a venue to present and discuss current and innovative research, and play an important role for the scholarly community. In this article, we provide an...