DeepSeek、ChatGPT、豆包、Kimi的“坦白局”：一场AI的“圆桌对话”（附提示词进阶技巧） 嘿，各位！今天我们四个AI——DeepSeek、ChatGPT、豆包和Kimi，来开个“坦白局”，聊聊我们各自的优点 …
谷歌除了发布Gemini 2.0 Flash，还给Gemini带了一项新能力： Deep Research。 Deep Research利用高级推理和长文本处理能力，可以充当个人的一个研究助理，比如用来做一些复杂的研究报告。 感 …
Purpose: To develop a deep-learning-based image reconstruction framework for reproducible research in MRI. Methods: The BART toolbox offers a rich set of implementations of calibration and reconstruction algorithms for parallel imaging and compress...
In this paper, we present a novel approach, called Deep MANTA (Deep Many-Tasks), for many-task vehicle analysis from a given image. A robust convolutional network is introduced for simultaneous vehicle detection, part localization, visibility charact...
Comprehensive deep-dive into Amazon Bedrock AgentCore. This workshop consists of tutorials to give you a deep understanding of AgentCore Services. All the labs are independent, so you can pick-and …
We give an overview of recent exciting achievements of deep reinforcement learning (RL). We discuss six core elements, six important mechanisms, and twelve applications. We start with background of machine learning, deep learning and reinforcement le...
The implementation of deep learning algorithms has brought new perspectives to plankton ecology. Emerging as an alternative approach to established methods, deep learning offers objective schemes to investigate plankton organisms in diverse environme...
Dataset distillation (DD) generates small synthetic datasets that can efficiently train deep networks with a limited amount of memory and compute. Despite the success of DD methods for supervised learning, DD for self-supervised pre-training of deep...
In this paper, we present a novel approach to kiwi fruit flower detection using Deep Neural Networks (DNNs) to build an accurate, fast, and robust autonomous pollination robot system. Recent work in deep neural networks has shown outstanding performa...
Although there exist several libraries for deep learning on graphs, they are aiming at implementing basic operations for graph deep learning. In the research community, implementing and benchmarking various advanced tasks are still painful and time-c...
We present SEDs, Spitzer colours, and IR luminosities for 850 micron selected galaxies in the GOODS-N field. Using the deep Spitzer Legacy images and new data and reductions of the VLA-HDF radio data, we find statistically secure counterparts for 6...
Ranking is the most important component in a search system. Mostsearch systems deal with large amounts of natural language data,hence an effective ranking system requires a deep understandingof text semantics. Recently, deep learning based natural la...
Apr 17, 2025 · This document provides a comprehensive technical overview of the DeepSeek-R1 repository, which contains a family of reasoning-specialized large language models. It covers the …
6 days ago · DeepSeek R1 Guide: Architecture, Benchmarks, and Practical Usage in 2026 DeepSeek R1 proved that open-source models can match closed-source reasoning capabilities. Released in …
Integrating large language models (LLMs) like DeepSeek R1 into healthcare requires rigorous evaluation of their reasoning alignment with clinical expertise. This study assesses DeepSeek R1's medical reasoning against expert patterns using 100 MedQA c...
Comprehensive deep-dive into Amazon Bedrock AgentCore. This workshop consists of tutorials to give you a deep understanding of AgentCore Services. All the labs are independent, so you can pick-and …
As deepfake technologies continue to advance, passive detection methods struggle to generalize with various forgery manipulations and datasets. Proactive defense techniques have been actively studied with the primary aim of preventing deepfake operat...
Deep learning has achieved a great success in many areas, from computer vision to natural language processing, to game playing, and much more. Yet, what deep learning is really doing is still an open question. There are a lot of works in this directi...
As the world seeks to become more sustainable, intelligent solutions are needed to increase the penetration of renewable energy. In this paper, the model-free deep reinforcement learning algorithm Rainbow Deep Q-Networks is used to control a battery...
Recently, deep learning models have increasingly been used in cognitive modelling of language. This study asks whether deep learning can help us to better understand the learning problem that needs to be solved by speakers, above and beyond linear me...