Deep Self-Taught Learning for Handwritten Character Recognition

Recent theoretical and empirical work in statistical machine learning has demonstrated the importance of learning algorithms for deep architectures, i.e., function classes obtained by composing multiple non-linear transformations. Self-taught learning (exploiting unlabeled examples or examples from other distributions) has already been applied to deep learners, but mostly to show the advantage of unlabeled examples. Here we explore the advantage brought by {\em out-of-distribution examples}. For this purpose we developed a powerful generator of stochastic variations and noise processes for character images, including not only affine transformations but also slant, local elastic deformations, changes in thickness, background images, grey level changes, contrast, occlusion, and various types of noise. The out-of-distribution examples are obtained from these highly distorted images or by including examples of object classes different from those in the target test set. We show that {\em deep learners benefit more from out-of-distribution examples than a corresponding shallow learner}, at least in the area of handwritten character recognition. In fact, we show that they beat previously published results and reach human-level performance on both handwritten digit classification and 62-class handwritten character recognition

Forest biodiversity, ecosystem functioning and the provision of ecosystem services

Forests are critical habitats for biodiversity and they are also essential for the provision of a wide range of ecosystem services that are important to human well-being. There is increasing evidence that biodiversity contributes to forest ecosystem functioning and the provision of ecosystem services. Here we provide a review of forest ecosystem services including biomass production, habitat provisioning services, pollination, seed dispersal, resistance to wind storms, fire regulation and mitigation, pest regulation of native and invading insects, carbon sequestration, and cultural ecosystem services, in relation to forest type, structure and diversity. We also consider relationships between forest biodiversity and multifunctionality, and trade-offs among ecosystem services. We compare the concepts of ecosystem processes, functions and services to clarify their definitions. Our review of published studies indicates a lack of empirical studies that establish quantitative and causal relationships between forest biodiversity and many important ecosystem services. The literature is highly skewed; studies on provisioning of nutrition and energy, and on cultural services, delivered by mixed-species forests are under-represented. Planted forests offer ample opportunity for optimising their composition and diversity because replanting after harvesting is a recurring process. Planting mixed-species forests should be given more consideration as they are likely to provide a wider range of ecosystem services within the forest and for adjacent land uses. This review also serves as the introduction to this special issue of Biodiversity and Conservation on various aspects of forest biodiversity and ecosystem services

Water quality.

<p>Water quality parameters at each caging site along the Bow River, Calgary, Alberta from September 12 to September 30, 2016. Values represent mean ± SEM (n = 8–9).</p

Sampling sites.

<p>Map of sampling locations along the Bow River, Alberta. Numbers represent locations where adult fathead minnows were caged relative to wastewater treatment plants (WWTP). Sampling locations consisted of two sites upstream of the City of Calgary wastewater treatment plants (BEAR: 51° 6'1.77"N, 114°16'24.18"W; CUSH: 51° 2'16.10"N, 114° 0'41.87"W), one site 15 m downstream of a WWTP side-bank discharge (GLEN: 51° 0'32.48"N, 114° 1'8.31"W), one site 250 m (H22X: 50°54'28.03"N, 114° 0'41.62"W) and one site approximately 18 km downstream from WWTP mid-channel diffusers (UPHI: 50°49'8.84"N, 113°47'31.76"W). Arrows indicate the direction of flow.</p

Fish morphometrics.

<p>Length (mm), weight (g) and condition factor of adult fathead minnows caged at each site along the Bow River, Calgary, Alberta. Values shown as mean ± SEM (n = 26–39).</p

Stress response.

<p>Whole-body cortisol (A), glucose (B), and lactate (C) content in adult fathead minnows caged at five sites along the Bow River, Alberta, from September to October 2016, prior to (0 min; orange boxplots) and after a standardized stressor (60 min; white boxplots). For each boxplot, the line within the box represents the median whole-body concentration (n = 7–10). The box ranges from the first to the third quartile (interquartile range), the whiskers extend to ±1.5 times the interquartile range, and values beyond this are denoted as black dots. Different letters indicate significant differences between sites (p<0.05). The inset indicates a significant main effect of time sampled post-stressor (TPS; p<0.05).</p

Proximate composition.

<p>Whole-body glycogen (A; n = 14–20) protein (B; n = 14–20) and lipid (C; n = 10–18) content in adult fathead minnows caged in the Bow River, Calgary, Alberta. For each boxplot, the line within the box represents the median whole-body concentration. The box ranges from the first to the third quartile (interquartile range), the whiskers extend to ±1.5 times the interquartile range, and values beyond this are denoted as black dots. Different letters indicate significant differences between sites (p<0.05).</p