The Experts below are selected from a list of 33675 Experts worldwide ranked by ideXlab platform
Patrick Cavanagh - One of the best experts on this subject based on the ideXlab platform.
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Compression of space for low visibility probes
Frontiers in Systems Neuroscience, 2016Co-Authors: Sabine Born, Hannah M Kruger, Eckart Zimmermann, Patrick CavanaghAbstract:Stimuli briefly flashed just before a saccade are perceived closer to the saccade target, a phenomenon known as perisaccadic Compression of space (Ross, Morrone, & Burr, 1997). More recently, we have demonstrated that brief probes are attracted towards a visual reference when followed by a mask, even in the absence of saccades (Zimmermann, Born, Fink, & Cavanagh, 2014). Here, we ask whether spatial Compression depends on the transient disruptions of the visual input stream caused by either a mask or a saccade. Both of these degrade the probe visibility but we show that low probe visibility alone causes Compression in the absence of any disruption. In a first experiment, we varied the regions of the screen covered by a transient mask, including areas where no stimulus was presented and a condition without masking. In all conditions, we adjusted probe contrast to make the probe equally hard to detect. Compression effects were found in all conditions. To Obtain Compression without a mask, the probe had to be presented at much lower contrasts than with masking. Comparing mislocalizations at different probe detection rates across masking, saccades and low contrast conditions without mask or saccade, Experiment 2 confirmed this observation and showed a strong influence of probe contrast on Compression. Finally, in Experiment 3, we found that Compression decreased as probe duration increased both for masks and saccades although here we did find some evidence that factors other than simply visibility as we measured it contribute to Compression. Our experiments suggest that Compression reflects how the visual system localizes weak targets in the context of highly visible stimuli.
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Compression of space for low visibility probes
Frontiers in Systems Neuroscience, 2016Co-Authors: Sabine Born, Hannah M Kruger, Eckart Zimmermann, Patrick CavanaghAbstract:Stimuli briefly flashed just before a saccade are perceived closer to the saccade target, a phenomenon known as perisaccadic Compression of space (Ross, Morrone, & Burr, 1997). More recently, we have demonstrated that brief probes are attracted towards a visual reference when followed by a mask, even in the absence of saccades (Zimmermann, Born, Fink, & Cavanagh, 2014). Here, we ask whether spatial Compression depends on the transient disruptions of the visual input stream caused by either a mask or a saccade. Both of these degrade the probe visibility but we show that low probe visibility alone causes Compression in the absence of any disruption. In a first experiment, we varied the regions of the screen covered by a transient mask, including areas where no stimulus was presented and a condition without masking. In all conditions, we adjusted probe contrast to make the probe equally hard to detect. Compression effects were found in all conditions. To Obtain Compression without a mask, the probe had to be presented at much lower contrasts than with masking. Comparing mislocalizations at different probe detection rates across masking, saccades and low contrast conditions without mask or saccade, Experiment 2 confirmed this observation and showed a strong influence of probe contrast on Compression. Finally, in Experiment 3, we found that Compression decreased as probe duration increased both for masks and saccades although here we did find some evidence that factors other than simply visibility as we measured it contribute to Compression. Our experiments suggest that Compression reflects how the visual system localizes weak targets in the context of highly visible stimuli.
Sabine Born - One of the best experts on this subject based on the ideXlab platform.
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Compression of space for low visibility probes
Frontiers in Systems Neuroscience, 2016Co-Authors: Sabine Born, Hannah M Kruger, Eckart Zimmermann, Patrick CavanaghAbstract:Stimuli briefly flashed just before a saccade are perceived closer to the saccade target, a phenomenon known as perisaccadic Compression of space (Ross, Morrone, & Burr, 1997). More recently, we have demonstrated that brief probes are attracted towards a visual reference when followed by a mask, even in the absence of saccades (Zimmermann, Born, Fink, & Cavanagh, 2014). Here, we ask whether spatial Compression depends on the transient disruptions of the visual input stream caused by either a mask or a saccade. Both of these degrade the probe visibility but we show that low probe visibility alone causes Compression in the absence of any disruption. In a first experiment, we varied the regions of the screen covered by a transient mask, including areas where no stimulus was presented and a condition without masking. In all conditions, we adjusted probe contrast to make the probe equally hard to detect. Compression effects were found in all conditions. To Obtain Compression without a mask, the probe had to be presented at much lower contrasts than with masking. Comparing mislocalizations at different probe detection rates across masking, saccades and low contrast conditions without mask or saccade, Experiment 2 confirmed this observation and showed a strong influence of probe contrast on Compression. Finally, in Experiment 3, we found that Compression decreased as probe duration increased both for masks and saccades although here we did find some evidence that factors other than simply visibility as we measured it contribute to Compression. Our experiments suggest that Compression reflects how the visual system localizes weak targets in the context of highly visible stimuli.
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Compression of space for low visibility probes
Frontiers in Systems Neuroscience, 2016Co-Authors: Sabine Born, Hannah M Kruger, Eckart Zimmermann, Patrick CavanaghAbstract:Stimuli briefly flashed just before a saccade are perceived closer to the saccade target, a phenomenon known as perisaccadic Compression of space (Ross, Morrone, & Burr, 1997). More recently, we have demonstrated that brief probes are attracted towards a visual reference when followed by a mask, even in the absence of saccades (Zimmermann, Born, Fink, & Cavanagh, 2014). Here, we ask whether spatial Compression depends on the transient disruptions of the visual input stream caused by either a mask or a saccade. Both of these degrade the probe visibility but we show that low probe visibility alone causes Compression in the absence of any disruption. In a first experiment, we varied the regions of the screen covered by a transient mask, including areas where no stimulus was presented and a condition without masking. In all conditions, we adjusted probe contrast to make the probe equally hard to detect. Compression effects were found in all conditions. To Obtain Compression without a mask, the probe had to be presented at much lower contrasts than with masking. Comparing mislocalizations at different probe detection rates across masking, saccades and low contrast conditions without mask or saccade, Experiment 2 confirmed this observation and showed a strong influence of probe contrast on Compression. Finally, in Experiment 3, we found that Compression decreased as probe duration increased both for masks and saccades although here we did find some evidence that factors other than simply visibility as we measured it contribute to Compression. Our experiments suggest that Compression reflects how the visual system localizes weak targets in the context of highly visible stimuli.
Stefan Heil - One of the best experts on this subject based on the ideXlab platform.
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Sequential neural text Compression
IEEE Transactions on Neural Networks, 1996Co-Authors: Jurgen Schmidhuber, Stefan HeilAbstract:The purpose of this paper is to show that neural networks may be promising tools for data Compression without loss of information. We combine predictive neural nets and statistical coding techniques to compress text files. We apply our methods to certain short newspaper articles and Obtain Compression ratios exceeding those of the widely used Lempel-Ziv algorithms (which build the basis of the UNIX functions "compress" and "gzip"). The main disadvantage of our methods is that they are about three orders of magnitude slower than standard methods.
Jurgen Schmidhuber - One of the best experts on this subject based on the ideXlab platform.
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Sequential neural text Compression
IEEE Transactions on Neural Networks, 1996Co-Authors: Jurgen Schmidhuber, Stefan HeilAbstract:The purpose of this paper is to show that neural networks may be promising tools for data Compression without loss of information. We combine predictive neural nets and statistical coding techniques to compress text files. We apply our methods to certain short newspaper articles and Obtain Compression ratios exceeding those of the widely used Lempel-Ziv algorithms (which build the basis of the UNIX functions "compress" and "gzip"). The main disadvantage of our methods is that they are about three orders of magnitude slower than standard methods.
Paul G Howard - One of the best experts on this subject based on the ideXlab platform.
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text image Compression using soft pattern matching
The Computer Journal, 1997Co-Authors: Paul G HowardAbstract:We present a method for both lossless and lossy Compression of bi-level images that consist mostly of printed or typed text. The key feature of the method is soft pattern matching, a way of making use of the information in previously encountered characters without risking the introduction of character substitution errors. We can Obtain lossless Compression which is about 20% better than that of the JBIG standard by direct application of this method. By allowing some loss based partly on the pattern matching using a technique called selective pixel reversal, we can Obtain Compression ratios about 2-4 times the Compression ratios of JBIG and 3-8 times those of G3 facsimile with no visible loss of quality. If used in facsimile machines, these Compression improvements would translate directly into communication cost reductions of the same factors, or into the capability of transmitting images at higher resolution with no increase in the number of bits sent.
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lossless and lossy Compression of text images by soft pattern matching
Data Compression Conference, 1996Co-Authors: Paul G HowardAbstract:We present a method for both lossless and lossy Compression of bilevel images that consist mostly of printed or typed text. The key feature of the method is soft pattern matching, a way of making use of the information in previously encountered characters without risking the introduction of character substitution errors. We can Obtain lossless Compression about 20 percent better than that of the JBIG standard by direct application of this method. By allowing some loss in a controlled manner based partly on the pattern matching, we can Obtain Compression ratios about two to four times the Compression ratios of JBIG and three to eight times those of G3 facsimile with no visible loss of quality.
