IEEE ICASSP 2024 Documents | SigPort

IEEE ICASSP 2024

IEEE ICASSP 2024 - IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) is the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The IEEE ICASSP 2024 conference will feature world-class presentations by internationally renowned speakers, cutting-edge session topics and provide a fantastic opportunity to network with like-minded professionals from around the world. Visit the website.

Advanced Search

Events on SigPort

BOOSTING ZERO-SHOT HUMAN-OBJECT INTERACTION DETECTION WITH VISION-LANGUAGE TRANSFER

Flow Dynamics Correction for Action Recognition

SEMANTIC DISTILLATION AND STRUCTURAL ALIGNMENT NETWORK FOR FAKE NEWS DETECTION

TNFORMER: SINGLE-PASS MULTILINGUAL TEXT NORMALIZATION WITH A TRANSFORMER DECODER MODEL

TokenMotion: Motion-Guided Vision Transformer For Video Camouflaged Object Detection Via Learnable Token Selection

ESA: Expert-and-Samples-Aware Incremental Learning under Longtail Distribution

Multi-Source Dynamic Interactive Network Collaborative Reasoning Image Captioning

Subspace-Based Co-Array Processing for Nested Arrays Without Eigendecomposition

UNCERTAINTY-GUIDED PERSON SEARCH MODEL WITH AUXILIARY SHALLOW FEATURE EXPLORATION

DATA DRIVEN GRAPHEME-TO-PHONEME REPRESENTATIONS FOR A LEXICON-FREE TEXT-TO-SPEECH

DATA DRIVEN GRAPHEME-TO-PHONEME REPRESENTATIONS FOR A LEXICON-FREE TEXT-TO-SPEECH

Speaker anonymization using neural audio codec language models

HAZY REMOTE SENSING IMAGES SEMANTIC SEGMENTATION FOR WEAKLY ANNOTATION BASED ON SALIENCY-AWARE ALIGNMENT STRATEGY

SEMANTIC SEGMENTATION FOR MULTI-SCENE REMOTE SENSING IMAGES WITH NOISY LABELS BASED ON UNCERTAINTY PERCEPTION

Enhancing Generalization in Medical Visual Question Answering Tasks via Gradient-Guided Model Perturbation

An Adapter-Based Unified Model for Multiple Spoken Language Processing Tasks

CONTEXTUAL BIASING OF NAMED-ENTITIES WITH LARGE LANGUAGE MODELS

RVAE-EM: Generative Speech Dereverberation Based On Recurrent Variational Auto-Encoder And Convolutive Transfer Function

S2E: Towards an End-to-End Entity Resolution Solution from Acoustic Signal

TOWARDS FASTER END-TO-END DATA TRANSMISSION OVER VOICE CHANNELS

Pages