Theory in Communication

1958

Citations in the corpus

• Deep learning in neural networks: An overview (2014, background): “, 1996), such as off-center-onsurround-like structures, as well as orientation sensitive edge detectors and Gabor filters (Gabor, 1946).”
• Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling (1998, methodology): “Our method is inspired by and bears some similarities to Heeger and Bergen’s (1995) recent work on texture synthesis, where many natural looking texture”
• Two‐dimensional adaptive Fourier decomposition (2014, background): “ms. The closed subspaces H2 ±(∂D) consist of, respectively, the functions of the form f± iHf,where His the Hilbert transformation of the context. Signals of the form f+iHfare called analytic signals ([6]). In relation to the Plemelj formula, the Hilbert transformation operator for a simply-connected”
• Scattering Representations for Recognition (2013, methodology): “Several methods exist in the literature, ranging from the Hilbert transform demodulation of Gabor [Gab46] to probabilistic demodulation methods, introduced in [Tur10], where a generative model is estimated.”
• Person Identification Technique Using Human Iris Recognition (2002, methodology): “To extract textual information of iris images, Daugman proposes using Gabor’s complex 2D Pass-band filters [9], which offer the best spatial-frequency resolution in the twodimensional case [10].”
• An Introduction to Wavelet Transform Tidal Analysis Methods (2000, unknown): “A short-time Fourier transform [STFT; also Gabor or Weyl-Heisenberg transform (Gabor, 1946)] divided a record into segments of equal length; each piece is separately Fourier transformed using an appropriate window g(t).”
• A phase-based approach to the estimation of the optical flow field using spatial filtering (2002, unknown): “Fleet and Jepson use spatiotemporal filter pairs to estimate the phase gradient and use a stability criterion that, among others, ensures that the instantaneous frequency [8] lies within the passband of the filter pairs.”
• Variational Mode Decomposition (2014, methodology): “The most prominent use of the Hilbert transform is in the construction of an analytic signal from a purely real signal, as proposed by Gabor [30].”
• Human age estimation using bio-inspired features (2009, background): “The Gabor functions [9] are usually taken for the S1 units [26] [28] [27] [22] [21], which provide a good model of cortical simple cell receptive fields.”
• Projective modules over noncommutative tori are multi-window Gabor frames for modulation spaces (2008, background): “Gabor analysis arose out of Gabor’s seminal work in [24] on the foundation of information theory.”
• Analyzing time–frequency relationship between oil price and exchange rate in Pakistan through wavelets (2015, unknown): “This issue has been resolved by Gabor [18], who advanced a specific transformation of Fourier transformation, which is also called a short-time Fourier transformation.”
• Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity (2000, methodology): “We are currently implementing our model on a two-dimensional vision system by using biologically inspired Gabor lters [20, 43].”
• A modified Gabor filter design method for fingerprint image enhancement (2003, unknown): “There are lots of papers published on its applications since Gabor (1946) proposed the 1-”
• Robust Object Recognition with Cortex-Like Mechanisms (2007, methodology): “For the most part, the use of visual neuroscience in computer vision has been limited to early vision for deriving stereo algorithms (e.g., [1]) and to justify the use of DoG (derivative-of-Gaussian) filters and more recently of Gabor filters [2], [3].”