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Found 17 papers, 7 papers with code
Towards Flexible, Scalable, and Adaptive Multi-Modal Conditioned Face Synthesis
Recent progress in multi-modal conditioned face synthesis has enabled the creation of visually striking and accurately aligned facial images.
Fuzzy Deep Hybrid Network for Fake News Detection
In this paper, we propose an innovative fuzzy logic-based hybrid model to improve the performance of fake news detection.
Wildfire Smoke Detection with Cross Contrast Patch Embedding
By using two different negative instance sampling strategies on positive images and negative images respectively, the problem of supervision signal confusion caused by label diversity in the process of network training is alleviated.
AROT-COV23: A Dataset of 500K Original Arabic Tweets on COVID-19
This paper presents a dataset called AROT-COV23 (ARabic Original Tweets on COVID-19 as of 2023) containing about 500, 000 original Arabic COVID-19-related tweets from January 2020 to January 2023.
CIRI: Curricular Inactivation for Residue-aware One-shot Video Inpainting
Video inpainting aims at filling in missing regions of a video.
Singularity: Planet-Scale, Preemptive and Elastic Scheduling of AI Workloads
At the heart of Singularity is a novel, workload-aware scheduler that can transparently preempt and elastically scale deep learning workloads to drive high utilization without impacting their correctness or performance, across a global fleet of AI accelerators (e. g., GPUs, FPGAs).
Toward Minimal Misalignment at Minimal Cost in One-Stage and Anchor-Free Object Detection
Common object detection models consist of classification and regression branches, due to different task drivers, these two branches have different sensibility to the features from the same scale level and the same spatial location.
3rd Place Solution to Google Landmark Recognition Competition 2021
In this paper, we show our solution to the Google Landmark Recognition 2021 Competition.
Prediction of Prognosis and Survival of Patients with Gastric Cancer by Weighted Improved Random Forest Model
Among the 10 public datasets, the Random Forest weighted in accuracy has the best performance on 6 datasets, with an average increase of 1. 44% in accuracy and an average increase of 1. 2% in AUC.
Enhancing 2D Representation via Adjacent Views for 3D Shape Retrieval
Multi-view shape descriptors obtained from various 2D images are commonly adopted in 3D shape retrieval.
Detection and Classification of Breast Cancer Metastates Based on U-Net
This paper presents U-net based breast cancer metastases detection and classification in lymph nodes, as well as patient-level classification based on metastases detection.
Infer Implicit Contexts in Real-time Online-to-Offline Recommendation
Understanding users' context is essential for successful recommendations, especially for Online-to-Offline (O2O) recommendation, such as Yelp, Groupon, and Koubei.
Rethinking Loss Design for Large-scale 3D Shape Retrieval
In this paper, we propose the Collaborative Inner Product Loss (CIP Loss) to obtain ideal shape embedding that discriminative among different categories and clustered within the same class.
Angular Triplet-Center Loss for Multi-view 3D Shape Retrieval
How to obtain the desirable representation of a 3D shape, which is discriminative across categories and polymerized within classes, is a significant challenge in 3D shape retrieval.
Learning Discriminative 3D Shape Representations by View Discerning Networks
In this network, a Score Generation Unit is devised to evaluate the quality of each projected image with score vectors.
Double Supervised Network with Attention Mechanism for Scene Text Recognition
In this paper, we propose Double Supervised Network with Attention Mechanism (DSAN), a novel end-to-end trainable framework for scene text recognition.
The APVA-TURBO Approach To Question Answering in Knowledge Base
In this paper, we study the problem of question answering over knowledge base.
