Search Results for author:
Found 19 papers, 9 papers with code
A Survey on 3D Reconstruction Techniques in Plant Phenotyping: From Classical Methods to Neural Radiance Fields (NeRF), 3D Gaussian Splatting (3DGS), and Beyond
Through this review, we aim to provide insights into how these diverse 3D reconstruction techniques can be effectively leveraged for automated and high-throughput plant phenotyping, contributing to the next generation of agricultural technology.
VLLFL: A Vision-Language Model Based Lightweight Federated Learning Framework for Smart Agriculture
By training a compact prompt generator to boost the performance of the VLM deployed across different farms, VLLFL preserves privacy while reducing communication overhead.
Modeling the Dynamics of Attentional Gamma Oscillations During the Encoding Process of Noise-Mixed Speech Signals
Using this model, we explored neural oscillation patterns in response to mixed speech stimuli and background noise.
Label Drop for Multi-Aspect Relation Modeling in Universal Information Extraction
Single-target instruction UIE enables the extraction of only one type of relation at a time, limiting its ability to model correlations between relations and thus restricting its capability to extract complex relations.
NOTA: Multimodal Music Notation Understanding for Visual Large Language Model
Based on the dataset, we trained NotaGPT, a music notation visual large language model.
Foundation Model-Based Apple Ripeness and Size Estimation for Selective Harvesting
The Fuji-Ripeness-Size Dataset and the apple detection and size estimation algorithms are made publicly available, which provides valuable benchmarks for future studies in automated and selective harvesting.
DeepContext: A Context-aware, Cross-platform, and Cross-framework Tool for Performance Profiling and Analysis of Deep Learning Workloads
This paper introduces DeepContext, a novel profiler that links program contexts across high-level Python code, deep learning frameworks, underlying libraries written in C/C++, as well as device code executed on GPUs.
The Music Maestro or The Musically Challenged, A Massive Music Evaluation Benchmark for Large Language Models
By leveraging ZIQI-Eval, we conduct a comprehensive evaluation over 16 LLMs to evaluate and analyze LLMs' performance in the domain of music.
Closed-loop control of gamma oscillations in the brain connections through the transcranial stimulations
The reconstruction of brain neural network connections occurs not only during the infancy and early childhood stages of brain development, but also in patients with cognitive impairment in middle and old age under the therapy with stimulated external interference, such as the non-invasive repetitive transcranial magnetic stimulation (rTMS) and the transcranial direct current stimulation(tDCS).
Performance Evaluation of Semi-supervised Learning Frameworks for Multi-Class Weed Detection
In this study, we assess the effectiveness of a semi-supervised learning framework for multi-class weed detection, employing two well-known object detection frameworks, namely FCOS and Faster-RCNN.
N-Gram Unsupervised Compoundation and Feature Injection for Better Symbolic Music Understanding
Experiment on various datasets demonstrate the effectiveness of our method and achieved state-of-the-art performance on a series of music understanding downstream tasks.
SoybeanNet: Transformer-Based Convolutional Neural Network for Soybean Pod Counting from Unmanned Aerial Vehicle (UAV) Images
Soybeans are a critical source of food, protein and oil, and thus have received extensive research aimed at enhancing their yield, refining cultivation practices, and advancing soybean breeding techniques.
Large Language Models and Foundation Models in Smart Agriculture: Basics, Opportunities, and Challenges
These models are trained on a large amount of data from multiple domains and modalities.
Deep Dynamic Epidemiological Modelling for COVID-19 Forecasting in Multi-level Districts
Results: We introduce four SEIR variants to fit different situations in different countries and regions.
Label-Efficient Learning in Agriculture: A Comprehensive Review
In addition, a systematic review of various agricultural applications exploiting these label-efficient algorithms, such as precision agriculture, plant phenotyping, and postharvest quality assessment, is presented.
HigeNet: A Highly Efficient Modeling for Long Sequence Time Series Prediction in AIOps
Modern IT system operation demands the integration of system software and hardware metrics.
Semantics-Preserved Distortion for Personal Privacy Protection in Information Management
In recent years, machine learning - particularly deep learning - has significantly impacted the field of information management.
Transition behavior of the seizure dynamics modulated by the astrocyte inositol triphosphate noise
Our simulation results show that the increase of the IP3 noise intensity induces the depolarization-block epileptic seizures together with an increase in neuronal firing frequency.
Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect
High performance multi-GPU computing becomes an inevitable trend due to the ever-increasing demand on computation capability in emerging domains such as deep learning, big data and planet-scale simulations.
Hardware Architecture Distributed, Parallel, and Cluster Computing Networking and Internet Architecture Performance
