Roseau[1] est urbs insulae Dominicae et caput civitatis liberae ex hac insula constitutae. Homines 14 725 anno 2011 hic habitabant[2]. Nomen Francogallice "arundo" sonat ex harundinetis ad ripas fluminis eiusdem nominis virentibus. Oppidum hic anno circiter 1700 a colonis Francicis conditum, ab anno fere 1800 sub imperio Britannico auctum est. Annis 1890 dignitatem urbis, a consilio urbano rectae, elevatum est.
Index
1Incolae notabiles
2Bibliographia
3Notae
4Nexus externi
Incolae notabiles |
Urbs Rosensis e nave in portu morante visa
Ioanna Rhys, scriptrix, hic nata anno 1890
Bibliographia |
Baedeker's Caribbean (Norvici: Jarrold, 1992) pp. 217-218
Barbara Marcolini, Drew Jordan, "Locals Describe Hurricane Maria’s Damage in Dominica" in New York Times (20 Septembris 2017)
Notae |
↑Vb. adiect. "Rosensis", cf.
"Dioecesis Rosensis" e The Hierarchy of the Catholic Church (situs a Davide M. Cheney elaboratus) .mw-parser-output .existinglinksgray a,.mw-parser-output .existinglinksgray a:visited{color:gray}.mw-parser-output .existinglinksgray a.new{color:#ba0000}.mw-parser-output .existinglinksgray a.new:visited{color:#a55858} (Anglice)
↑Anni 2011 populatio et census - Officium Statisticum Centrale (Dominica) - lectum 10 Oct. 2017[1]
Nexus externi |
Vicimedia Communia plura habent quae ad Roseau spectant.
Situs geographici et historici: • GeoNames
Niko Lipsanen, Naturalistic and existential realms of place in Roseau, Dominica (2001)
Imagines urbis Rosensis
Urbes Americae Septentrionalis capitales
Ordine alphabetico enumeratae: Basseterre • Belmopanum • Castries • Dominicopolis • urbs Guatimalensis • Havana • Kingstown • Managua • Mexicopolis • Nassau • Ottavia • urbs Panamensis • Pontipolis • Portus Hispaniae • Portus Principis • Regiopolis • Roseau • urbs Sancti Georgii • urbs Sancti Ioannis • urbs Sancti Iosephi • urbs Sancti Salvatoris • Tegucigalpa • Vasingtonia
Sub civitatum nominibus annexae: Antiqua et Barbuda • insulae Bahamenses • Barbata • Beliza • Canada • Civitates Foederatae Americae • Cuba • Dominica • res publica Dominicana • Granata • Guatimalia • Haitia • Honduria • Iamaica • Mexicum • Nicaragua • Costarica • Panama • Salvatoria • Sancta Lucia • Sanctus Christophorus et Nives • Sanctus Vincentius et Granatinae • Trinitas et Tabacum
Opus geopoliticum • Urbes orbis terrarum capitales
Capsae cognatae: Urbes Americae Septentrionalis maximae • Urbes Africae capitales • Urbes Americae Australis capitales • Urbes Asiae capitales • Urbes Europae capitales • Urbes Oceaniae capitales
Tabula multilinguis Rosettana in Museo Britannico ostenditur. Tabula Rosettana, [1] etiam titulo OGIS 90 agnita, est stela decreto de rebus sacris in Aegypto anno 196 a.C.n. lato inscripta. Tabula iuxta Rosettam Aegypti, urbem in delta Nili et ad oram maris Mediterranei iacentem, anno 1799 a milite Francico reperta est. Inventio stelae, linguis duabus scripturisque tribus inscriptae, eruditis Instituti Aegypti statim nuntiata est; ibi enim iussu imperatoris Napoleonis eruditi omnium scientiarum (sub aegide Commissionis Scientiarum et Artium) properaverant cum expeditione Francica. Qua a Britannis mox debellata, tabula Rosettana Londinium missa hodie apud Museum Britannicum iacet. Textus Graecus cito lectus interpretationi textuum Aegyptiorum (in formis hieroglyphica et demotica expressorum) gradatim adiuvit. Denique textum plene interpretatus est Ioannes Franciscus Champollion. Ab opere eruditorum cumulativo coepit hodiernus scripturae hieroglyphicae linguaeque Aegyptiae a...
1
$begingroup$
This is what I mean as document text image: I want to label the texts in image as separate blocks and my model should detect these labels as classes. NOTE: This is how the end result should be like: The labels like Block 1, Block 2, Block 3,.. should be Logo, Title, Date,.. Others, etc. Work done: First approach : I tried to implement this method via Object Detection, it didn't work. It didn't even detect any text. Second approach : Then I tried it using PixelLink. As this model is build for scene text detection, it detected each and every text in the image. But this method can detect multiple lines of text if the threshold values are increased. But I have no idea how do I add labels to the text blocks. PIXEL_CLS_WEIGHT_all_ones = 'PIXEL_CLS_WEIGHT_all_ones' PIXEL_C...
1
$begingroup$
I have this LSTM model model = Sequential() model.add(Masking(mask_value=0, input_shape=(timesteps, features))) model.add(LSTM(100, dropout=0.2, recurrent_dropout=0.2, return_sequences=False)) model.add(Dense(features, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy']) and shapes X_train (21, 11, 5), y_train (21, 5) . Each timestep is represented by 5 features and return_sequences is set to False because I want to predict one 5D array (the next timestep) for each input sequence of 11 timesteps. I get the error ValueError: y_true and y_pred have different number of output (5!=1) If I reshape the data as X_train (21, 11, 5), y_train (21, 1, 5) instead I get the error ValueError: Inva...
Roseau
