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For implanted neural-sensing devices, one of the remaining challenges is to transmit stable power/data (P/D) transmission for high spatiotemporal resolution neural data. This paper presents a miniaturized implantable 128-channel wireless neural-sensing microsystem using TSV-embedded dissolvable μ-needle array, a flexible interposer and 4 dies by 2.5D/3D TSV heterogeneous SiP technology. The 4 dies...
The Remote Access Trojan (RAT), whose exposure often lags far behind its widespread infection, plays a part in the growing number of cyber-attacks. In terms of intrusion detection, signature-based methods still occupy the dominant position together with anomaly-based methods that are deployed to be complementary. The anomaly-based methods are efficient and resource saving, however, anomaly-based RAT...
This paper reports a novel research that uses the wavelet invariant moments of the motion templates representing walking figure to determine representative features for gait recognition. Changes of pedestrian silhouettes covering one stride are decomposed into disappear and emergent image area, from which motion history is cumulated into static grey scale images as motion templates. These motion templates...
The main issue of video copy detection is to estimate a constant spatial-temporal transformation in object level between the original video and the copies. In this paper, we propose a multi-level trajectory modeling approach for video copy detection. It includes a rich trajectory description and a robust trajectory-to-trajectory matching to preserve and explore the trajectory characteristics in both...
With the proliferation of online media services, ad video has become an important way to promote various products, services and ideas. Research efforts have been devoted to the contextual advertising whereas comprehensive recommendation of video ads is less exploited. In this paper, we propose to establish a semantic linking between video ads and relevant product/service online in a cross-media manner...
With the proliferation of online media services, video ads are pervasive across various platforms involving Internet services and interactive TV services. Existing research efforts such as Google AdSense and MSRA videosense/imagesense have been devoted to the less intrusive insertion of relevant textual or video ads in streams or Web pages through text/image/video content analysis whereas the inherent...
In this paper, for every local feature, we propose to learn its similar local features across all positive images, instead of using heuristic distance as similarity measure. Specifically, multiple instance learning (MIL) is employed to simultaneously determine the similar points of a local feature and learn its corresponding discriminative function which can be regarded as some kind of similarity...
In content-based image retrieval, the method based on salient points detection is one of the most active research areas for it can represent the local properties of the image. This paper proposes an improved salient points detector based on wavelet transform which can extract salient points more exactly. Then, an annular segmentation algorithm based on salient points distribution is designed, which...
The appearance of a surface texture is strongly dependent on the illumination direction. This is why current state-of-art surface texture classification methods require multiple training images captured under a variety of illumination conditions for each class. This paper presents an inexpensive method for illumination-invariant texture classification based on self-similarity and wavelet transform...
In content-based image retrieval, how to representation of local properties in an image is one of the most active research issues. In certain circumstance, however, users concern more about objects of their interest and only wish to retrieve images containing relevant objects, while ignoring irrelevant image areas (such as the background). Previous work on represent of local properties normally requires...
In this paper, we propose a statistical gait feature fusion approach for human recognition by gait. First, we produce a gait period estimation function by converting the contour of silhouette in specific regions into an ID signal, and divide each silhouette sequence into cycles. With a novel shape descriptor while retaining translation, scale and rotation invariance, a statistical feature extraction...
This paper describes a novel feature representation method for gait analysis and recognition applications. By tiling one-period gait subsequence in a 2D polar-plane along a ring frame by frame, a gait appearance model is built. The model consists of structural information of individual silhouette and contextual silhouettes centered at the current frame in the polar-plane. With an invariant histogram-based...
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