1 citations · 1 across the 7 of their papers we have counts for
8 papers
Frequency-Aware Dual-Stream Learning for Balanced Realism and Fidelity in Electron Microscopy Imaging
Longmi Gao, Zhengkai Zhao, Pan Gao +1
Electron microscopy enables nanoscale cellular visualization but faces a trade-off between imaging resolution and acquisition speed. Existing learning-based methods rely on single-…
Novel quantum circuit for image compression utilizing modified Toffoli gate and quantized transformed coefficient alongside a novel reset gate
Ershadul Haque, Manoranjan Paul
Quantum image computing has emerged as a groundbreaking field, revolutionizing how we store and process data at speeds incomparable to classical methods. Nevertheless, as image siz…
PALQA: A Novel Parameterized Position-Aware Lossy Quantum Autoencoder using LSB Control Qubit for Efficient Image Compression
Ershadul Haque, Manoranjan Paul, Faranak Tohidi +2
With the growing interest in quantum computing, quantum image processing technology has become a vital research field due to its versatile applications and ability to outperform cl…
Att2CPC: Attention-Guided Lossy Attribute Compression of Point Clouds
Kai Liu, Kang You, Pan Gao +1
With the great progress of 3D sensing and acquisition technology, the volume of point cloud data has grown dramatically, which urges the development of efficient point cloud compre…
Global Attention-Guided Dual-Domain Point Cloud Feature Learning for Classification and Segmentation
Zihao Li, Pan Gao, Kang You +2
Previous studies have demonstrated the effectiveness of point-based neural models on the point cloud analysis task. However, there remains a crucial issue on producing the efficien…
Predicting Heart Failure with Attention Learning Techniques Utilizing Cardiovascular Data
Ershadul Haque, Manoranjan Paul, Faranak Tohidi
Cardiovascular diseases (CVDs) encompass a group of disorders affecting the heart and blood vessels, including conditions such as coronary artery disease, heart failure, stroke, an…
Impact analysis of recovery cases due to COVID19 using LSTM deep learning model
Md Ershadul Haque, Samiul Hoque
The present world is badly affected by novel coronavirus (COVID-19). Using medical kits to identify the coronavirus affected persons are very slow. What happens in the next, nobody…
Advance quantum image representation and compression using DCTEFRQI approach
Md Ershadul Haque, Manoranjon Paul, Anwaar Ulhaq +1
In recent year, quantum image processing got a lot of attention in the field of image processing due to opportunity to place huge image data in quantum Hilbert space. Hilbert space…