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Generative Model Driven Representation Learning in a Hybrid Framework for Environmental Audio Scene and Sound Event Recognition

The analysis of sound information is helpful for audio surveillance, multimedia information retrieval, audio tagging, and forensic applications. Environmental audio scene recognition (EASR) and sound event recognition (SER) for audio surveillance are challenging tasks due to the presence of multiple sound sources, background noises, and the existence of overlapping or polyphonic contexts.

Deep Dual-Channel Neural Network for Image-Based Smoke Detection

Smoke detection plays an important role in industrial safety warning systems and fire prevention. Due to the complicated changes in the shape, texture, and color of smoke, identifying the smoke from a given image still remains a substantial challenge, and this has accordingly aroused a considerable amount of research attention recently.

Style-Controlled Synthesis of Clothing Segments for Fashion Image Manipulation

We propose an approach for digitally altering people's outfits in images. Given images of a person and a desired clothing style, our method generates a new clothing item image. The new item displays the color and pattern of the desired style while geometrically mimicking the person's original item. Through superimposition, the altered image is made to look as if the person is wearing the new item.

Multi-Focus Image Fusion by Hessian Matrix Based Decomposition

In this paper, a Hessian matrix based multi-focus image fusion method is proposed. First, the integral map is introduced for fast compute the Hessian matrix of source images at different scales, and the multi-scale Hessian matrix of source image is obtained. Second, the multi-scale Hessian matrix is used to decompose each source image into two kinds of regions: the feature and background regions.

Postdoctoral Fellowship Machine Learning & Artificial Intelligence: Constraints (2 Positions)

64888 - CSIRO Postdoctoral Fellowship in Machine Learning and Artificial Intelligence: Constraints. (2 Positions)
  • Do you have experience in Machine Learning and Artificial Intelligence?
  • Work with world class researchers to solve the world’s biggest challenges
  • Join CSIRO’s Data61, the largest data innovation group in Australia
CSIRO Early Research Career (CERC) Postdoctoral Fellowships provide opportunities to scientists and engineers who have completed their doctorate and have less than three years relevant postdoctoral work experience.

PhD position in signal processing and machine learning at the SAMPL Lab, Weizmann

The department of mathematics and computer science at the Weizmann Institute invites students for a PhD position in the areas of signal processing and machine learning with applications in communications, radar, medical imaging and optical imaging. The selected candidate will work with Prof. Yonina Eldar at the SAMPL lab. In the area of medical imaging, the work will be performed in close collaboration with leading hospitals in Israel and abroad. Some of the topics will be in close collaboration with PIs at MIT, Stanford and the Broad Institute.

Post-doc position in signal processing and machine learning at the SAMPL Lab, Weizmann

The department of mathematics and computer science at the Weizmann Institute invites researchers for a postdoctoral position in the area of signal processing and machine learning with applications in communications, radar, medical imaging and optical imaging. The selected candidate will work with Prof. Yonina Eldar at the SAMPL lab. In the area of medical imaging, the work will be performed in close collaboration with leading hospitals in Israel and abroad. Some of the topics will be in close collaboration with PIs at MIT, Stanford and the Broad Institute.